docs: def print_benchmark(n_train, n_test, n_dim, res):
      """ Print the benchmarks
  
      Parameters
      ----------
      n_train : int
        number of points in the training set
      n_test : int
        number of points in the test set
      n_dim : int
        number of dimensions (default=2)
      res : dict
        a dictionary with the timing results
      """
      print('='*80)
      print(' '*10, 'N_dim={}, N_train={}, N_test={}'.format(n_dim,
                                                             n_train, n_test))
      print('='*80)
      print('\n', '# Training the model', '\n')
      print('|'.join(['{:>11} '.format(el) for el in ['t_train (s)'] +
                      VARIOGRAM_MODELS]))
      print('-' * (11 + 2) * (len(VARIOGRAM_MODELS) + 1))
      print('|'.join(['{:>11} '.format('Training')] +
                     ['{:>11.2} '.format(el) for el in
                      [res['t_train_{}'.format(mod)]
                       for mod in VARIOGRAM_MODELS]]))
  
      print('\n', '# Predicting kriging points', '\n')
      print('|'.join(['{:>11} '.format(el) for el in ['t_test (s)'] + BACKENDS]))
      print('-' * (11 + 2) * (len(BACKENDS) + 1))
  
      for n_closest_points in N_MOVING_WINDOW:
          timing_results = [res.get(
              't_test_{}_{}'.format(mod, n_closest_points), '')
                            for mod in BACKENDS]
          print('|'.join(['{:>11} '.format('N_nn=' + str(n_closest_points))] +
                         ['{:>11.2} '.format(el) for el in timing_results]))